Artificial intelligence (AI) has transformed organizations across industries, and perhaps nowhere are we seeing its transformative powers so clearly as in customer relationship management. AI is increasingly enabling organizations to improve customer service, improve customer loyalty and free customer service agents to focus on higher-value tasks. In doing so, AI unlocks a wide range of benefits, from reduced costs and improved employee retention to higher revenue and increased customer satisfaction.
The COVID-19 pandemic only accelerated digital transformation and the adoption of AI in the contact center. Gartner predicts that "by 2022, 70% of customer interactions will involve emerging technologies such as machine learning (ML) applications, chatbots and mobile messaging, up from 15% in 2018."
Amid widespread shutdowns, new types of interactions emerged, such as in the financial industry, where agents fielded an influx of calls from customers who were furloughed or laid off, or in retail, where supply chain disruptions and store closures led to numerous customer complaints. In addition, the move to widespread remote and hybrid work models means that supervisors can no longer physically look over the agent's shoulder or readily have on-the-floor conversations if the agent runs into trouble—they now have less direct oversight over how agents are performing.
The use of AI technology in the contact center has now moved from a nice-to-have to an imperative due to its ability to transform customer service, both in terms of quality as well as efficiency. Self-service enabled many contact centers to cope with spikes in volume during the pandemic.
While machine learning examines and compares data to find patterns and explore nuances, AI takes it a step further, continually evolving in how it enables machines to behave in a way previously thought to require human intelligence.
How AI Is Revolutionizing Customer Service
The applications of AI in customer service are wide-ranging, with use cases that include:
- Leveraging bots: Organizations are increasingly using bots to better understand and respond to the people they are interacting with. Unlike basic chatbots that rely on rules, AI chatbots rely on natural language understanding, natural language processing and natural language generation, and they get smarter over time with use. Among the key benefits of AI chatbots are consistency of response—bots will answer the same question from two customers in the same way, while agents’ responses to customers may vary—and a lack of waiting time.
- Understanding and scoring agent behaviors that influence customer satisfaction metrics during an interaction: By helping agents understand the behaviors that affect customer satisfaction—for example, showing empathy or building rapport—and giving them in-the-moment guidance, contact centers can give employees the guidance they need to drive meaningful conversations and self-improve. This, in turn, enables the organization to both better serve customers and increase the job satisfaction of its employees.
- Anticipating and acting on customer needs: AI-enabled analytics predict and surface customer trends as well as unlock accurate, consistent customer insights by analyzing 100% of millions of unstructured interactions across multiple channels. With prescriptive insights throughout the customer lifecycle, organizations can leverage analytics and AI to improve every moment of the customer’s journey with the business.
- Understand customer sentiment: AI can be trained to recognize sentiment—and to continue to learn and evolve. Sentiment scoring, which is a proven predictive indicator of customer satisfaction, such as transactional NPS or CSAT surveys, allows the organization to analyze customer interactions to uncover areas in the business that need improvement, monitor areas critical to customer loyalty and retention, and monitor agent behaviors. It can also identify interactions that start positive and move to negative, or vice versa, to allow organizations to perform root cause analysis.
- Route customers intelligently: Customers are increasingly using chat, social and SMS in addition to voice channels, and they expect organizations to know their preferences and shape their experiences accordingly. Smart omnichannel routing gives organizations a rich understanding of customer preferences and matches them with the most suitable agent on the customer’s preferred channel, using AI to predict emotion and intent. AI also enables organizations to proactively reach out to customers with a highly customized experience.
Key Benefits of AI in Customer Support
Across these use cases for AI in customer service, organizations are realizing a variety of benefits, including:
- Empowering agents to deliver great service: AI models can be used to interpret and measure the human behaviors proven to influence customer satisfaction. Machine learning continuously identifies behavioral patterns with models that get smarter with every interaction. AI can then guide agents in real-time to self-correct during the interaction, giving them confidence in their performance while enabling them to proactively improve.
- Augmenting existing staff: Most requests today can be handled by a bot; they do not require human interaction (for example: store hours, package tracking information, return policies etc.). The vast majority of interactions can be automated or handled by a bot, which frees employees to focus on more complex customer requests.
- Improved staff retention and loyalty: AI removes much of the repetitive work associated with customer service, enabling employees to do what they do best—connect with customers and make decisions that require a human touch. More than three-quarters (77%) of agents surveyed recently by Salesforce for its Fourth Edition of the State of Service report said they believe that automating routine tasks allows them to focus on more complex work—up from the 69% who agreed in an earlier survey in 2018. This type of work creates employees who are more fulfilled, and thus less likely to leave the organization.
- Increased revenue: Years of experience in the industry have shown that when customers are happier, revenue increases. In addition, contact centers can use AI to understand where a customer is in their lifecycle as well as relevant data, such as the topic of recent inquiries, to alert agents to possible sales opportunities, driving revenue.
- Better self-service: AI and analytics continuously learn from past interactions to improve future self-service experiences. AI-enabled technology builds better self-service by enabling contact centers to:
- Review every interaction, not just a sampling.
- Identify the most important aspects of interactions for self-service.
- Recognize the highest priorities to automate in self-service.
- Gather the specific words and phrases needed to update self-service.
- Improved time to resolution: Bots run by AI can better understand the context of a conversation, so it never needs to go to an agent. This also helps reduce repeat calls. In fact, one entertainment company that integrated AI into its contact center operations realized a 5% increase in first-call resolution, a key metric that had a benefit of $8.7M
- Improved customer satisfaction: Across the board, AI is revolutionizing how contact centers engage with their customers and deliver a more personalized, more proactive customer experience. One telecommunications provider that integrated AI into its contact center operations realized a 2-point increase in their transactional NPS score in just four months.
The Bottom Line: AI Has Changed Customer Support Forever
AI has revolutionized customer support, creating a wider divide between those companies able to capitalize on the promise of AI and those struggling to leverage it, McKinsey asserts, and the revolution is only expected to continue to expand in breadth and scope in the contact center. An increasing number of organizations are using bots as a first line of defense in customer service. They’re also tapping into AI to understand and score the human behaviors that impact the customer experience and customer satisfaction; anticipating and acting on customer needs; unlocking the ability to understand customer-empowered agents; increasing revenue; and more.